Condition-Based Maintenance Optimisation for Queensland’s Railways. Rail maintainers currently use time-based (scheduled) approaches to balance the costs and benefits of inspections and maintenance. Changing to condition-based maintenance has the potential to reduce costs and improve track condition. This project aims to enable this approach for rail by developing: 1) new track degradation prediction techniques combining Big Data and engineering knowledge; 2) new on-board sensing capabilities fo ....Condition-Based Maintenance Optimisation for Queensland’s Railways. Rail maintainers currently use time-based (scheduled) approaches to balance the costs and benefits of inspections and maintenance. Changing to condition-based maintenance has the potential to reduce costs and improve track condition. This project aims to enable this approach for rail by developing: 1) new track degradation prediction techniques combining Big Data and engineering knowledge; 2) new on-board sensing capabilities for frequent, low-cost track monitoring; 3) novel inspection and maintenance optimisation methods to efficiently allocate resources. The knowledge generated by this project is expected to decrease maintenance costs, safety risk, and track closures and therefore enhance the affordability and reliability of rail travel.Read moreRead less
Nonlinear frequency mixing methods for materials and damage evaluation. This project aims to investigate new approaches for frequency mixing in nonlinear ultrasonics, and to demonstrate their potential for the non-destructive evaluation of material degradation and early damage detection. The anticipated outcomes will be increased detection sensitivity relative to current inspection techniques and an enhanced capability for quantifying the damage. This will provide the basis for more cost efficie ....Nonlinear frequency mixing methods for materials and damage evaluation. This project aims to investigate new approaches for frequency mixing in nonlinear ultrasonics, and to demonstrate their potential for the non-destructive evaluation of material degradation and early damage detection. The anticipated outcomes will be increased detection sensitivity relative to current inspection techniques and an enhanced capability for quantifying the damage. This will provide the basis for more cost efficient safety management of high-value assets and infrastructure, and for enhancing Australia’s competitiveness in advanced manufacturing.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE210100273
Funder
Australian Research Council
Funding Amount
$407,679.00
Summary
Supercomputing to understand track buckling and related train derailments. This project aims to understand the contributions of railway train forces to a dangerous and high-cost track dynamic behaviour called buckling; by developing a supercomputing method that unlocks the capability for large-scale 3D train-track interaction research for railway trains of up to 250 vehicles. This project expects to generate new knowledge regarding track buckling, train derailments and train-track dynamics. Expe ....Supercomputing to understand track buckling and related train derailments. This project aims to understand the contributions of railway train forces to a dangerous and high-cost track dynamic behaviour called buckling; by developing a supercomputing method that unlocks the capability for large-scale 3D train-track interaction research for railway trains of up to 250 vehicles. This project expects to generate new knowledge regarding track buckling, train derailments and train-track dynamics. Expected outcomes include a new supercomputing method for train-track dynamics and derailment research and a science-based technique to assess track buckling safety. This project should provide significant benefits to the rail industry including enhanced rail safety, lower maintenance costs and improved transport efficiency.Read moreRead less
A new role for vibration analysis in gear wear modelling and prediction. This project aims to improve prediction of the remaining useful life of gears. Gears are widely used in industry and transport. This project aims to integrate the two main methods of gear condition monitoring, vibration and oil analysis, and perform model-based wear prediction with the tribology and dynamic models continually updated on the basis of measured wear debris and vibration. New signal processing tools should allo ....A new role for vibration analysis in gear wear modelling and prediction. This project aims to improve prediction of the remaining useful life of gears. Gears are widely used in industry and transport. This project aims to integrate the two main methods of gear condition monitoring, vibration and oil analysis, and perform model-based wear prediction with the tribology and dynamic models continually updated on the basis of measured wear debris and vibration. New signal processing tools should allow estimation of relatively weak friction forces, previously neglected, as an important prognostic tool. This would allow detailed root cause analysis and prediction of remaining useful life. Improvements in gear prognosis would have safety and economic benefits by eliminating unforeseen catastrophic failures and optimising maintenance schedules.Read moreRead less